Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm
Abstract. An expectation maximization (EM) algorithm is proposed to find fibre length distributions in standing trees. The available data come from cylindric wood samples (increment cores). The sample contains uncut fibres as well as fibres cut once or twice. The sample contains not only fibres, but...
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crwiley:10.1111/j.1467-9469.2006.00501.x 2024-09-09T19:59:41+00:00 Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm SVENSSON, INGRID SJÖSTEDT‐DE LUNA, SARA BONDESSON, LENNART 2006 http://dx.doi.org/10.1111/j.1467-9469.2006.00501.x https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1467-9469.2006.00501.x https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1467-9469.2006.00501.x en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Scandinavian Journal of Statistics volume 33, issue 3, page 503-522 ISSN 0303-6898 1467-9469 journal-article 2006 crwiley https://doi.org/10.1111/j.1467-9469.2006.00501.x 2024-06-18T04:16:55Z Abstract. An expectation maximization (EM) algorithm is proposed to find fibre length distributions in standing trees. The available data come from cylindric wood samples (increment cores). The sample contains uncut fibres as well as fibres cut once or twice. The sample contains not only fibres, but also other cells, the so‐called ‘fines’. The lengths are measured by an automatic fibre‐analyser, which is not able to distinguish fines from fibres and cannot tell if a cell has been cut. The data thus come from a censored version of a mixture of the fine and fibre length distributions in the tree. The parameters of the length distributions are estimated by a stochastic version of the EM algorithm, and an estimate of the corresponding covariance matrix is derived. The method is applied to data from northern Sweden. A simulation study is also presented. The method works well for sample sizes commonly obtained from increment cores. Article in Journal/Newspaper Northern Sweden Wiley Online Library Scandinavian Journal of Statistics 33 3 503 522 |
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Wiley Online Library |
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English |
description |
Abstract. An expectation maximization (EM) algorithm is proposed to find fibre length distributions in standing trees. The available data come from cylindric wood samples (increment cores). The sample contains uncut fibres as well as fibres cut once or twice. The sample contains not only fibres, but also other cells, the so‐called ‘fines’. The lengths are measured by an automatic fibre‐analyser, which is not able to distinguish fines from fibres and cannot tell if a cell has been cut. The data thus come from a censored version of a mixture of the fine and fibre length distributions in the tree. The parameters of the length distributions are estimated by a stochastic version of the EM algorithm, and an estimate of the corresponding covariance matrix is derived. The method is applied to data from northern Sweden. A simulation study is also presented. The method works well for sample sizes commonly obtained from increment cores. |
format |
Article in Journal/Newspaper |
author |
SVENSSON, INGRID SJÖSTEDT‐DE LUNA, SARA BONDESSON, LENNART |
spellingShingle |
SVENSSON, INGRID SJÖSTEDT‐DE LUNA, SARA BONDESSON, LENNART Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm |
author_facet |
SVENSSON, INGRID SJÖSTEDT‐DE LUNA, SARA BONDESSON, LENNART |
author_sort |
SVENSSON, INGRID |
title |
Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm |
title_short |
Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm |
title_full |
Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm |
title_fullStr |
Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm |
title_full_unstemmed |
Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm |
title_sort |
estimation of wood fibre length distributions from censored data through an em algorithm |
publisher |
Wiley |
publishDate |
2006 |
url |
http://dx.doi.org/10.1111/j.1467-9469.2006.00501.x https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1467-9469.2006.00501.x https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1467-9469.2006.00501.x |
genre |
Northern Sweden |
genre_facet |
Northern Sweden |
op_source |
Scandinavian Journal of Statistics volume 33, issue 3, page 503-522 ISSN 0303-6898 1467-9469 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1111/j.1467-9469.2006.00501.x |
container_title |
Scandinavian Journal of Statistics |
container_volume |
33 |
container_issue |
3 |
container_start_page |
503 |
op_container_end_page |
522 |
_version_ |
1809930768289366016 |